An Imaging HF GPR Using Stationary Antennas: Experimental Validation Over the Antarctic Ice Sheet
Bibliographic record
Abstract
Terrestrial And Planetary Imaging Radar (TAPIR) is an innovative high-frequency ground-penetrating radar (GPR) developed in the frame of the Martian NetLander mission to probe the subsurface down to kilometric depths. Unlike most GPRs, TAPIR is able to image underground reflectors with stationary antennas. In this paper, after a brief presentation of the instrument, we describe the method developed to interpret data collected during the RAdar of NEtlander in Terre AdÉlie (RANETA) field survey in Antarctica. This method consists of retrieving the direction of arrival of each detected echo through the measurement of five components of the electromagnetic field (the three magnetic components and the horizontal components of the electric field). Thus, both the range and the direction of each individual reflection or diffraction due to the ice–bedrock interface are resolved. We validated this method on finite-difference time-domain numerically simulated data for different subsurface configurations before applying it to RANETA observations. In particular, the irregular topography of the bedrock in two sounding sites was revealed. We discuss the accuracy of our results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".